Lymph Node Metastasis In Breast Cancer Research Articles

Integrin profle of circulating tumour cells in breast cancer patients

Background. Integrins, as adhesion molecules, play a key role in the interaction of cells with the basal membrane and intercellular matrix. Numerous studies demonstrate evidence of increased expression of integrins on tumor cells in different types of cancer. Thus, β3 and αV integrins are associated with stem-like features of tumor cells, and β4 integrin as α6β4 heterodimer provides anchorage-independent survival of malignant mammary epithelial cells. However, all the described functions of integrins have been investigated exclusively on primary tumor cells. The functional significance and expression pattern of integrins on circulating tumor cells (CTCs) remains unclear. The aim of the study was to evaluate the β3, β4 and αvβ5 integrin expression on CTCs and its association with molecular subtype, stage and lymph node metastasis in breast cancer patients Material and Methods. The study included 22 patients with T1–4N0–3M0 invasive ductal breast carcinoma. Venous blood was taken from patients without neoadjuvant chemotherapy (group 1) and after neoadjuvant chemotherapy (group 2) in the volume of 12 ml into vacuum tubes with EDTA. The expression of CTC integrins including stemness features CD44/CD24, CD133 and ALDH1, and epithelial-mesenchymal transition (EMT) (N-cadherin) was evaluated by flow cytometry. Results. CTCs with β3+β4-αvβ5- and β3-β4+αvβ5+ phenotypes and stemness properties were associated with larger tumor size (T4) in breast cancer patients. The β3 integrin expression was associated with more aggressive molecular subtypes of breast cancer. Administration of neoadjuvant chemotherapy did not affect the expression pattern of β3, β4 and αvβ5 integrins in CTCs. Conclusion. In breast cancer, most CTCs expressed β3, β4 and αvβ5 integrins despite the lack of attachment to the basal membrane and intercellular matrix. The expression of the above integrins on CTCs was associated with breast cancer molecular subtype, stage and lymph node metastasis, and therefore its evaluation can be considered as one of the objectives of liquid biopsy study.

Comparison of the Performance of [18F]-FDG PET/CT and [18F]-FDG PET/MRI for Lymph Node Metastasis in Breast Cancer: A Systematic Review and Meta- Analysis.

The primary objective of this study was to conduct a comparative analysis of the diagnostic efficacy of [18F]-FDG PET/CT and [18F]-FDG PET/MRI in the detection of breast cancer lymph node metastasis. We conducted a comprehensive search on PubMed, Embase, and Web of Science databases, encompassing eligible articles until March 2023. The pooled sensitivity and specificity for [18F]-FDG PET/CT and [18F]-FDG PET/MRI have been reported as estimates with 95% Confidence Intervals (CIs) using a bivariate random-effect model. Utilizing the I square (I2) statistic, heterogeneity among pooled studies was evaluated. The quality assessment of the included studies was conducted using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) methodology. We included 18 studies (2057 patients). The sensitivity, specificity, and AUC (Area Under the Curve) values of [18F]-FDG PET/CT for overall lymph node metastasis in breast cancer have been found to be 0.58 (0.39 - 0.75), 0.83 (0.69-0.92), and 0.79 (0.75-0.82), respectively. Correspondingly, the values for [18F]-FDG PET/MRI were found to be 0.76 (0.60-0.88), 0.85 (0.77-0.91), and 0.89 (0.86-0.91), respectively. The sensitivity, specificity, and AUC values of [18F]-FDG PET/CT for axillary lymph node metastasis in breast cancer were 0.52 (0.37-0.67), 0.84 (0.68-0.92), and 0.73 (0.69-0.76), respectively. Correspondingly, the values for [18F]-FDG PET/MRI were 0.84 (0.76-0.89), 0.87 (0.75-0.94), and 0.86 (0.83-0.89), respectively. This study has suggested [18F]-FDG PET/MRI to have greater diagnostic power than [18F]-FDG PET/CT in detecting lymph node metastasis in breast cancer. However, the [18F]-FDG PET/MRI results have been obtained from a small sample size study, and more and larger prospective studies are needed for further confirmation on this issue.</p>.

Expressions and clinical significance of CCN5 and E-cadherin in primary and recurrent lesions of breast cancer.

Breast cancer recurrence and lymph node metastasis significantly impact patient outcomes. Understanding the molecular mechanisms behind these processes is crucial for developing effective treatments. CCN5 and E-cadherin are proteins involved in cell adhesion and epithelial-mesenchymal transition (EMT), playing roles in breast cancer progression. This study aimed to analyze the expression levels and clinical significance of CCN5 and E-cadherin in primary and recurrent breast cancer lesions. Immunohistochemical staining using the SP method was performed to detect CCN5 and E-cadherin expression levels in 28 normal breast tissue samples, 52 primary breast cancer lesions, and paired recurrent chest wall lesions. The expression levels of these proteins were compared across different tissue types and correlated with lymph node metastasis. CCN5 and E-cadherin expression levels significantly differed among normal breast tissues, primary breast cancer lesions, and recurrent lesions (Χ2 = 18.934 and Χ2 = 14.516, p < 0.05). Primary breast cancer lesions exhibited higher CCN5 and E-cadherin expression levels compared with recurrent lesions and normal tissues, although these differences were not statistically significant. Patients without lymph node metastases exhibited significantly higher expression levels of CCN5 and E-cadherin compared with those with lymph node metastases (Χ2 = 9.775, Χ2 = 9.1479, p < 0.05). A positive correlation between CCN5 and E-cadherin expression levels was found in breast cancer tissues (r = 0.398, p < 0.001). CCN5 and E-cadherin were expressed at lower levels in recurrent breast cancer tissues and those with lymph node metastases, indicating their potential roles in breast cancer recurrence and metastasis. These findings suggest that CCN5 and E-cadherin might work synergistically to influence breast cancer progression.

Feasibility Study on Detecting Breast Cancer Lymph Node Metastasis and Optimizing Nursing Workflow.

This study explores using AI for detecting lymph node metastasis in breast cancer, aiming to analyze extensive medical imaging data. AI assists clinicians in identifying metastases and formulating precise treatment plans. Employing image analysis and machine learning, the research assesses AI's potential to recognize patterns within medical imaging data. The study evaluates the feasibility of integrating AI-based detection into diagnostic workflows. Collaborative efforts with hospitals include collecting annotated breast cancer lymph node data, optimizing workflows, and clinically validating results. Anticipated outcomes aim to highlight AI's crucial role in enhancing early detection and treatment decisions for breast cancer patients. Anticipated results aim to underscore the crucial role of AI in improving early detection and treatment decision-making for breast cancer patients while optimizing efficiency in the operating room nursing workflow.

A novel nomogram and survival analysis for different lymph node status in breast cancer based on the SEER database

IntroductionThe axillary lymph node status (ALNS) and internal mammary lymph nodes (IMLN) expression associated with breast cancer are closely linked to prognosis. This study aimed to establish a nomogram to predict survival at 3, 5, and 10 years in patients with various lymph node statuses.MethodsWe obtained data from patients with breast cancer between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER database). Chi-square analysis was performed to test for differences in the pathological characteristics of the groups, and Kaplan–Meier analysis and the log-rank test were used to plot and compare the correlation between overall survival (OS) and breast cancer specific survival (BCSS). The log-rank test was used for the univariate analysis, and statistically significant characteristics were included in the multivariate and Cox regression analyses. Finally, Independent factor identification was included in constructing the nomogram using R studio 4.2.0; area under curve (AUC) values were calculated, and receiver operating characteristic (ROC) curve, calibration, and decision curve analysis (DCA) curves were plotted for evaluation.ResultsA total of 279,078 patients were enrolled and analysed, demonstrating that the isolated tumour cells (ITC) group had clinicopathological characteristics similar to those of micrometastases (Mic). Multivariate analysis was performed to identify each subgroup's independent risk factors and construct a nomogram. The AUC values were 74.7 (95% CI 73.6–75.8), 72.8 (95% CI 71.9–73.8), and 71.2 (95% CI 70.2–72.2) for 3-, 5-, and 10-year OS, respectively, and 82.2 (95% CI 80.9–83.6), 80.1 (95% CI 79.0–81.2), and 75.5 (95% CI 74.3–76.8) for BCSS in overall breast cancer cases, respectively. AUC values for 3-, 5-, and 10-year OS in the ITC group were 64.8 (95% CI 56.5–73.2), 67.7 (95% CI 62.0–73.4), and 65.4 (95% CI 60.0–70.7), respectively. For those in the Mic group, AUC values for 3-, 5-, and 10-year OS were 72.9 (95% CI 70.7–75.1), 72.4 (95% CI 70.6–74.1), and 71.3 (95% CI 69.6–73.1), respectively, and AUC values for BCSS were 77.8 (95% CI 74.9–80.7), 75.7 (95% CI 73.5–77.9), and 70.3 (95% CI 68.0–72.6), respectively. In the IMLN group, AUC values for 3-, 5-, and 10-year OS were 75.2 (95% CI 71.7–78.7), 73.4 (95% CI 70.0–76.8), and 74.0 (95% CI 69.6–78.5), respectively, and AUC values for BCSS were 76.6 (95% CI 73.0–80.3), 74.1 (95% CI 70.5–77.7), and 74.7 (95% CI 69.8–79.5), respectively. The ROC, calibration, and DCA curves verified that the nomogram had better predictability and benefits.ConclusionThis study is the first to investigate the predictive value of different axillary lymph node statuses and internal mammary lymph node metastases in breast cancer, providing clinicians with additional aid in treatment decisions.

Artificial Intelligence Helps Pathologists Increase Diagnostic Accuracy and Efficiency in the Detection of Breast Cancer Lymph Node Metastases.

The detection of lymph node metastases is essential for breast cancer staging, although it is a tedious and time-consuming task where the sensitivity of pathologists is suboptimal. Artificial intelligence (AI) can help pathologists detect lymph node metastases, which could help alleviate workload issues. We studied how pathologists' performance varied when aided by AI. An AI algorithm was trained using more than 32 000 breast sentinel lymph node whole slide images (WSIs) matched with their corresponding pathology reports from more than 8000 patients. The algorithm highlighted areas suspicious of harboring metastasis. Three pathologists were asked to review a dataset comprising 167 breast sentinel lymph node WSIs, of which 69 harbored cancer metastases of different sizes, enriched for challenging cases. Ninety-eight slides were benign. The pathologists read the dataset twice, both digitally, with and without AI assistance, randomized for slide and reading orders to reduce bias, separated by a 3-week washout period. Their slide-level diagnosis was recorded, and they were timed during their reads. The average reading time per slide was 129 seconds during the unassisted phase versus 58 seconds during the AI-assisted phase, resulting in an overall efficiency gain of 55% ( P <0.001). These efficiency gains are applied to both benign and malignant WSIs. Two of the 3 reading pathologists experienced significant sensitivity improvements, from 74.5% to 93.5% ( P ≤0.006). This study highlights that AI can help pathologists shorten their reading times by more than half and also improve their metastasis detection rate.

Porphyrin-Based Self-Assembled Nanoparticles for PET/MR Imaging of Sentinel Lymph Node Metastasis.

Diagnosing of lymph node metastasis is challenging sometimes, and multimodal imaging offers a promising method to improve the accuracy. This work developed porphyrin-based nanoparticles (68Ga-F127-TAPP/TCPP(Mn) NPs) as PET/MR dual-modal probes for lymph node metastasis imaging by a simple self-assembly method. Compared with F127-TCPP(Mn) NPs, F127-TAPP/TCPP(Mn) NPs synthesized by amino-porphyrins (TAPP) doping can not only construct PET/MR bimodal probes but also improve the T1 relaxivity (up to 456%). Moreover, T1 relaxivity can be adjusted by altering the molar ratio of TAPP/TCPP(Mn) and the concentration of F127. However, a similar increase in T1 relaxivity was not observed in the F127-TCPP/TCPP(Mn) NPs, which were synthesized using carboxy-porphyrins (TCPP) doping. In a breast cancer lymph node metastasis mice model, subcutaneous injection of 68Ga-F127-TAPP/TCPP(Mn) NPs through the hind foot pad, the normal lymph nodes and metastatic lymph nodes were successfully distinguished based on the difference of PET standard uptake values and MR signal intensities. Furthermore, the dark brown F127-TAPP/TCPP(Mn) NPs demonstrated the potential for staining and mapping lymph nodes. This study provides valuable insights into developing and applying PET/MR probes for lymph node metastasis imaging.

Retrospective Evaluation of the Preoperative Features of Breast Cancer and Sentinel Lymph Node Metastasis

Retrospective Evaluation of the Preoperative Features of Breast Cancer and Sentinel Lymph Node Metastasis

Lymph node metastasis prediction and biological pathway associations underlying DCE-MRI deep learning radiomics in invasive breast cancer.

The relationship between the biological pathways related to deep learning radiomics (DLR) and lymph node metastasis (LNM) of breast cancer is still poorly understood. This study explored the value of DLR based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in LNM of invasive breast cancer. It also analyzed the biological significance of DLR phenotype based on genomics. Two cohorts from the Cancer Imaging Archive project were used, one as the training cohort (TCGA-Breast, n = 88) and one as the validation cohort (Breast-MRI-NACT Pilot, n = 57). Radiomics and deep learning features were extracted from preoperative DCE-MRI. After dual selection by principal components analysis (PCA) and relief methods, radiomics and deep learning models for predicting LNM were constructed by the random forest (RF) method. A post-fusion strategy was used to construct the DLR nomograms (DLRNs) for predicting LNM. The performance of the models was evaluated using the receiver operating characteristic (ROC) curve and Delong test. In the training cohort, transcriptome data were downloaded from the UCSC Xena online database, and biological pathways related to the DLR phenotypes were identified. Finally, hub genes were identified to obtain DLR gene expression (RadDeepGene) scores. DLRNs were based on area under curve (AUC) evaluation (training cohort, AUC = 0.98; validation cohort, AUC = 0.87), which were higher than single radiomics models or GoogLeNet models. The Delong test (radiomics model, P = 0.04; GoogLeNet model, P = 0.01) also validated the above results in the training cohorts, but they were not statistically significant in the validation cohort. The GoogLeNet phenotypes were related to multiple classical tumor signaling pathways, characterizing the biological significance of immune response, signal transduction, and cell death. In all, 20 genes related to GoogLeNet phenotypes were identified, and the RadDeepGene score represented a high risk of LNM (odd ratio = 164.00, P < 0.001). DLRNs combining radiomics and deep learning features of DCE-MRI images improved the preoperative prediction of LNM in breast cancer, and the potential biological characteristics of DLRN were identified through genomics.

Investigating the role of tumour-to-skin proximity in predicting nodal metastasis in breast cancer

BackgroundUnderstanding the factors influencing nodal status in breast cancer is vital for axillary staging, therapy, and patient survival. The nodal stage remains a crucial factor in prognostication indices. This study investigates the relationship between tumour-to-skin distance (in T1–T3 tumours where the skin is not clinically involved) and the risk of nodal metastasis.MethodsWe retrospectively reviewed data from 100 patients who underwent neoadjuvant chemotherapy (NACT). Besides patient demographics and tumour variables, a radiologist retrospectively reviewed pre-operative MRI to measure tumour-to-skin distance. R core packages were used for univariate (χ2 and T-Wilcoxon tests) and bivariate logistic regression statistical analysis.ResultsOf 95 analysable datasets, patients’ median age was 51 years (IQR: 42–61), 97% were symptomatic (rest screen detected), and the median tumour size was 43 mm (IQR, 26–52). On multivariate analysis, increasing invasive tumour size (p = 0.02), ER positivity (p = 0.007) and shorter tumour-to-skin distance (p = 0.05) correlated with nodal metastasis. HER2 was not included in multivariate analysis as there was no association with nodal status on univariate analysis. In node-positive tumours, as tumour size increased, the tumour-to-skin distance decreased (r = − 0.34, p = 0.026). In node-negative tumours, there was no correlation (r = + 0.18, p = 0.23).ConclusionThis study shows that non-locally advanced cancers closer to the skin (and consequent proximity to subdermal lymphatics) are associated with a greater risk of nodal metastasis. Pre-operative identification of those more likely to be node positive may suggest the need for a second-look USS since a higher nodal stage may lead to a change in therapeutic strategies, such as upfront systemic therapy, node marking, and axillary clearance without the need to return to theatre following sentinel node biopsy.

Discordance of Biomarker Expression Profile between Primary Breast Cancer and Synchronous Axillary Lymph Node Metastasis in Preoperative Core Needle Biopsy

Background: Breast cancer (BC) is a heterogeneous disease made up of clones with different metastatic potential. Intratumoral heterogeneity may cause metastases to show divergent biomarker expression, potentially affecting chemotherapy response. Methods: We investigated the immunohistochemical (IHC) and FISH profile of estrogen receptors (ER), progesterone (PR) receptors, Ki67, and HER2 in a series of BC-matched primary tumors (PTs) and axillary lymph node (ALN) metastases in pre-operative core needle biopsies (CNBs). Phenotypical findings were correlated to morphological features and their clinical implications. Results: Divergent expression between PTs and ALNs was found in 10% of the tumors, often involving multiple biomarkers (12/31, 39%). Most (52%) displayed significant differences in ER and PR staining. HER2 divergences were observed in almost three-quarters of the cases (23/31, 74%), with five (16%) switching from negativity to overexpression/amplification in ALNs. Roughly 90% of disparities reflected significant morphological differences between PTs and ALN metastases. Less than half of the discrepancies (12/31, 39%) modified pre/post-operative treatment options. Conclusions: We observed relevant discrepancies in biomarker expression between PTs and metastatic ALNs in a noteworthy proportion (10%) of preoperative BC CNBs, which were often able to influence therapies. Hence, our data suggest routine preoperative assessment of biomarkers in both PTs and ALNs in cases showing significant morphological differences.

DOP66 INSPIRE: Preliminary data from an observational post-marketing registry on the effectiveness and safety of darvadstrocel in patients with Crohn’s Disease and complex perianal fistulas

Abstract Background Darvadstrocel (DVS), a suspension of expanded allogeneic adipose-derived mesenchymal stem cells, is approved for the treatment of complex Crohn’s perianal fistulas (CPF). INSPIRE (EUPAS24267) is a European observational post-approval study evaluating real-world effectiveness and safety of DVS in patients with complex CPF for up to 36 months. Here we report preliminary clinical and safety outcomes from INSPIRE. Methods Patients with complex CPF who had received DVS according to local standard practice were eligible to enrol. Clinical response (closure of ≥50% of external openings [EOs]) and clinical remission (closure of all EOs) of DVS-treated fistulas that were draining at baseline, were evaluated in the all-treated (AT; received ≥1 dose of DVS with an evaluation for fistula response after 6 months) and per-protocol (PP; received DVS as per label-approved guidelines) cohorts. Treatment-emergent adverse events (TEAEs), serious TEAEs and AEs of special interest were reported for the safety cohort (all patients treated with DVS). Results As of April 2023, 652 patients had enrolled (Table 1). Complete data to evaluate 12-month clinical response and remission were available for 134 (AT cohort) and 124 (PP cohort) patients, of whom 79.9% (AT, n = 107) and 79.8% (PP, n = 99) had a clinical response and 76.1% (AT, n = 102) and 76.6% (PP, n = 95) had clinical remission (Figure 1). From baseline to Month 12, there was a decrease in the mean (standard deviation [SD]) Perianal Disease Activity Index score (–3.5 [3.3]; n/N = 96/302 and –3.7 [3.2]; n/N = 89/249) and a decrease in the mean (SD) Harvey–Bradshaw Index for Crohn’s disease activity (-0.3 [2.8]; n/N = 102/302 and -0.4 [2.9]; n/N = 95/249) in the AT and PP cohorts, respectively. Complete safety data were available for 619 patients (median [min–max] follow-up 480 [6–1595]) days. Overall, 26% (n = 162) had ≥1 TEAE and 10% (n = 63) ≥1 serious TEAE. The most frequent TEAEs were anal abscess (6.9%), COVID-19 (1.9%) and proctalgia (1.1%). No deaths were reported. One breast cancer lymph node metastasis and one ovarian epithelial cancer were reported; both events were confounded by immunosuppressant treatment and were not considered related to DVS treatment. Conclusion These preliminary data are consistent with the pivotal ADMIRE-CD study and demonstrate a single dose of DVS in patients with complex CPF is associated with positive clinical outcomes in up to 80% of patients, and a favourable safety profile, both of which are maintained after 12 months. The inherent limitations of registry-based studies mean these data should be interpreted with caution. However, the ongoing INSPIRE study will provide longer follow-up data to confirm these observations with respect to any study limitations.

Optimization of supraclavicular lymph node clinical target volume delineation in high-risk breast cancer: a single center experience and recommendation

BackgroundProphylactic irradiation of supraclavicular lymph node drainage areas can improve the regional control rate of lymph node-positive or lymph node-negative disease but a locally-advanced stage breast cancer, and it can reduce breast cancer-related mortality. However, many controversies exist in the clinical target volume delineation of supraclavicular lymph node drainage in patients with breast cancer.MethodsWe retrospectively analyzed 42 patients with breast cancer and supraclavicular lymph node metastasis at our hospital between January 2017 and December 2021. Among these cases, 32 were locally advanced and 10 were stage IV at initial treatment. A patient with breast cancer who did not undergo dissection of the supraclavicular and infraclavicular lymph nodes at our hospital was selected as a standard patient. A contrast-enhanced computed tomography (CT) scan for positioning was used as a template image, and blood vessels, muscles, and bony landmarks were used as references for positioning. The metastatic supraclavicular lymph nodes were identified in all enrolled patients and projected into the template CT images.ResultsThe metastastic pattern of supraclavicular lymph node in breast cancer was proposed: distribution along the posterolateral border of the internal jugular vein (medial supraclavicular group) and along the transverse jugular vein (lateral supraclavicular group). We theorized that the lateral and posterior borders of the clinical target volume in the supraclavicular region should include the lymph nodes in the posterior triangle of the neck (level V) in high-risk individuals. If the metastatic axillary lymph node is extensive, then the superior border of the supraclavicular region should be moved upward appropriately.ConclusionsThis study analyzed patients with breast cancer and supraclavicular lymph node metastasis at initial treatment, explored the metastastic pattern of supraclavicular lymph node, and applied anatomical knowledge to further optimize the target volume delineation of supraclavicular lymph node drainage area in high-risk breast cancer.

SIX1 amplification modulates stemness and tumorigenesis in breast cancer

BackgroundSine oculis homeobox homolog 1 (SIX1) is a transcription factor that has recently been identified as a crucial regulator of embryonic development and tumorigenesis. SIX1 is upregulated in different types of tumors, including breast cancer. However, the role and mechanism of SIX1 upregulation in breast cancer carcinogenesis remains uncertain.MethodsIn this study, we utilized various databases such as UALCAN, TCGA, STRING, and Kaplan–Meier Plotter to investigate the mRNA expression, prognosis, transcriptional profile changes, signal pathway rewiring, and interaction with cancer stem cells of SIX1 in breast cancer. We also conducted both in vitro and in vivo experiments to validate its positive regulation effect on breast cancer stem cells.ResultsOur findings demonstrated that the expression of SIX1 varies among different subtypes of breast cancer and that it upregulates breast cancer grading and lymph node metastasis. Besides, SIX1 participates in the rewiring of several cancer signaling pathways, including estrogen, WNT, MAPK, and other pathways, and interacts with cancer stem cells. SIX1 showed a significant positive correlation with breast cancer stem cell markers such as ALDH1A1, EPCAM, ITGB1, and SOX2. Moreover, our in vitro and in vivo experiments confirmed that SIX1 can promote the increase in the proportion of stem cells and tumor progression.ConclusionsAltogether, our results suggest that SIX1 plays an essential regulatory role in breast cancer's occurrence, and its amplification can be utilized as a diagnostic and prognostic predictor. The interaction between SIX1 and cancer stem cells may play a critical role in regulating breast cancer's initiation and metastasis.

Nonmetastatic Axillary Lymph Nodes Have Distinct Morphology and Immunophenotype in Obese Patients with Breast Cancer at Risk for Metastasis

Obese breast cancer patients have worse outcomes than their normal weight counterparts, with a 50% to 80% increased rate of axillary nodal metastasis. Recent studies suggest a link between increased lymph node adipose tissue and breast cancer nodal metastasis. Further investigation into potential mechanisms underlying this link may reveal potential prognostic utility of fat-enlarged lymph nodes in breast cancer patients. This study uses a deep learning model to identify morphological differences in non-metastatic axillary nodes between obese, node-positive and node-negative breast cancer patients. The model was developed using nested cross-validation on 180 cases and achieved an AUC of 0.67 in differentiating patients using hematoxylin and eosin stained whole-slide images. The top predictive patches from the slides according to the model were reviewed by a pathologist and their morphological differences were quantified. This analysis showed an increased average adipocyte size (p-value=0.004), increased white space between lymphocytes (p-value<0.0001), and increased red blood cells (p-value<0.001) in non-metastatic lymph nodes of node-positive patients. Preliminary immunohistochemistry analysis on a subset of 30 patients showed a trend of decreased CD3 expression and increased leptin expression in fat-replaced axillary lymph nodes of obese, node-positive patients. These findings suggest a novel direction to further investigate the interaction between lymph node adiposity, lymphatic dysfunction, and breast cancer nodal metastases, highlighting a possible prognostic tool for obese breast cancer patients.

Optical Imaging in Human Lymph Node Specimens for Detecting Breast Cancer Metastases: A Review.

Assessment of regional lymph node status in breast cancer is of important staging and prognostic value. Even though formal histological examination is the currently accepted standard of care, optical imaging techniques have shown promising results in disease diagnosis. In the present article, we review six spectroscopic techniques and focus on their use as alternative tools for breast cancer lymph node assessment. Elastic scattering spectroscopy (ESS) seems to offer a simple, cost-effective, and reproducible method for intraoperative diagnosis of breast cancer lymph node metastasis. Optical coherence tomography (OCT) provides high-resolution tissue scanning, along with a short data acquisition time. However, it is relatively costly and experimentally complex. Raman spectroscopy proves to be a highly accurate method for the identification of malignant axillary lymph nodes, and it has been further validated in the setting of head and neck cancers. Still, it remains time-consuming. Near-infrared fluorescence imaging (NIRF) and diffuse reflectance spectroscopy (DFS) are related to significant advantages, such as deep tissue penetration and efficiency. Fourier-transform infrared spectroscopy (FTIR) is a promising method but has significant drawbacks. Nonetheless, only anecdotal reports exist on their clinical use for cancerous lymph node detection. Our results indicate that optical imaging methods can create informative and rapid tools to effectively guide surgical decision-making.

Development of lymph node metastasis-related prognostic markers in breast cancer

BackgroundLymph node metastasis (LNM) from Breast cancer (BC) is commonly seen in BC progression. Currently, the identification of genes linked with LNM in BC remains in mystery. MethodsGenes related to BC LNM were screened, and a risk model was constructed based on LASSO-Cox analysis. Combined with the Kaplan-Meier curve, the ability of riskscore to distinguish different baseline characteristics was evaluated, and model was verified by the receiver operating characteristic (ROC) curve. The expression levels of prognostic marker genes were analyzed by qRT-PCR and western blot (WB). ResultsA higher survival rate and longer survival time in low-risk BC patients. The 1, 3 and 5 year AUC values of the training set were 0.79, 0.74, and 0.73, respectively. Results for the validation set was similar to the training set. The differentially expressed genes between the high- and low-risk groups were significantly enriched in immune pathways. In addition, the low-risk group had higher levels of immune infiltration. qRT-PCR and WB results showed that in BC, CDH10, SMR3A, POU3F2, and FABP7 were down-regulated, and LHX1 was up-regulated. ConclusionsWe built a prognostic model of BC based on LNM-related genes, proffering evaluation for prognosis and precise cure of BC. SignificanceAt present, the genes related to lymph node metastasis in BC are still largely unknown and need to be further explored. Searching for potential lymph node metastasis-related genes of BC will provide meaningful biomarkers for BC treatment. Based on TCGA-BRCA data, we established an effective 11-gene prognostic risk model that could predict patient outcomes independently. Our model could classify BC patients and distinguish patients with poor prognosis effectively. Besides, the feature genes we identified might exert a predictive function in immunotherapy. The results of this study provide a new reference for the prognosis and treatment of BC patients with lymph node metastasis.

Correlation between the risk of lymph node metastasis and the expression of GBP1 in breast cancer patients.

To explore the prognostic value and correlation between the risk of lymph node metastasis (LNM) and Guanylate-binding Protein 1 (GBP1) in breast cancer (BC) patients. In this retrospective study, the clinical data of 150 patients with BC who were surgically resected in The Affiliated Qingdao Central Hospital of Qingdao University from January 2019 to December 2021 were included. Patients were divided into metastasis group (n=110) or non-metastasis group (n=40) according to whether there was LNM post-surgery. Logistic regression was used to analyze the risk factors for LNM in BC, and Kaplan-Meier was used to assess the risk of disease progression 12 months post-operation in both groups. Patients were divided into a GBP1 low expression-group (n=75) or a GBP1 high expression-group (n=75). The risk of disease progression, one-year post-surgery was analyzed, and the predictive value of GBP1 in BC tissue was assessed by the receiver operating characteristics (ROC) curve. Independent risk factors for BC with LNM were GBP1, CEA and TNM stage (P<0.05). There is a linear relationship between GBP1 expression and LNM risk in BC (χ2=0.88, P<0.05). Patients with high expression of GBP1 had a higher risk of LNM (χ2=3.204, P<0.001) and early postoperative progression (χ2=7.412, P<0.05). The AUC of GBP1 in predicting the risk of LNM was 0.840. Patients with BC and a higher expression of GBP1 could be at an increased risk of LNM. Elevations in GBP1 expression can also suggest a poor prognosis for patients with BC.

Construction of a comprehensive predictive model for axillary lymph node metastasis in breast cancer: a retrospective study

PurposeThe accurate assessment of axillary lymph node metastasis (LNM) in early-stage breast cancer (BC) is of great importance. This study aimed to construct an integrated model based on clinicopathology, ultrasound, PET/CT, and PET radiomics for predicting axillary LNM in early stage of BC.Materials and methods124 BC patients who underwent 18 F-fluorodeoxyglucose (18 F-FDG) PET/CT and whose diagnosis were confirmed by surgical pathology were retrospectively analyzed and included in this study. Ultrasound, PET and clinicopathological features of all patients were analyzed, and PET radiomics features were extracted to establish an ultrasound model (clinicopathology and ultrasound; model 1), a PET model (clinicopathology, ultrasound, and PET; model 2), and a comprehensive model (clinicopathology, ultrasound, PET, and radiomics; model 3), and the diagnostic efficacy of each model was evaluated and compared.ResultsThe T stage, US_BIRADS, US_LNM, and PET_LNM in the positive axillary LNM group was significantly higher than that of in the negative LNM group (P = 0.013, P = 0.049, P < 0.001, P < 0.001, respectively). Radiomics score for predicting LNM (RS_LNM) for the negative LNM and positive LNM were statistically significant difference (-1.090 ± 0.448 vs. -0.693 ± 0.344, t = -4.720, P < 0.001), and the AUC was 0.767 (95% CI: 0.674–0.861). The ROC curves showed that model 3 outperformed model 1 for the sensitivity (model 3 vs. model 1, 82.86% vs. 48.57%), and outperformed model 2 for the specificity (model 3 vs. model 2, 82.02% vs. 68.54%) in the prediction of LNM. The AUC of mode 1, model 2 and model 3 was 0.687, 0.826 and 0.874, and the Delong test showed the AUC of model 3 was significantly higher than that of model 1 and model 2 (P < 0.05). Decision curve analysis showed that model 3 resulted in a higher degree of net benefit for all the patients than model 1 and model 2.ConclusionThe use of a comprehensive model based on clinicopathology, ultrasound, PET/CT, and PET radiomics can effectively improve the diagnostic efficacy of axillary LNM in BC. Trial registration: This study was registered at ClinicalTrials Gov (number NCT05826197) on 7th, May 2023.

Risk factors of breast cancer recurrence in pathologic complete response achieved by patients following neoadjuvant chemotherapy: a single-center retrospective study.

Pathologic complete response (pCR) of breast cancer after neoadjuvant chemotherapy (NAC) is highly related to molecular subtypes. Patients who achieved tumor pCR after NAC have a better prognosis. However, despite of better prognosis, pCR patients have a potential for recurrence. There is little evidence of risk factors of recurrence in patients with pCR. We aim to analyze factors associated with tumor recurrence in patients who achieved pCR. This study retrospectively reviewed the data of patients diagnosed with breast cancer who achieved pCR after receiving NAC between January 2009 and December 2018 in Samsung Medical Center. pCR was defined as no residual invasive cancer in the breast and axillary nodes even if there is residual ductal carcinoma in situ (ypT0 or ypTis with ypN0). Breast cancers are classified into 4 subtypes based on hormone receptors (HR) and human epithelial growth factor receptor 2 (HER2) status. Patients who had bilateral breast cancer, ipsilateral supraclavicular or internal mammary lymph node metastasis, inflammatory breast cancer, distant metastasis, unknown subtype, and histologically unique case were excluded from the study. In total 483 patients were included in this study except for patients who corresponded to the exclusion criteria. The median follow-up duration was 59.0 months (range, 0.5-153.3 months). Breast cancer recurred in 4.1% of patients (20 of 483). There was a significant difference in clinical T (P = 0.004) and clinical N (P = 0.034) stage in the Kaplan-Meier curve for disease-free survival. Molecular subtypes (P = 0.573), Ki67 (P = 1.000), and breast surgery type (P = 0.574) were not associated with tumor recurrence in patients who achieved pCR after NAC. In the clinical T stage and clinical N stage, there was a significant difference between recurrence and no-recurrence groups (clinical T stage; P = 0.045, clinical N stage; P = 0.002). Univariable Cox regression revealed statistical significance in the clinical T stage (P = 0.049) and clinical N stage (P = 0.010), while multivariable Cox regression demonstrated non-significance in the clinical T stage (P = 0.320) and clinical N stage (P = 0.073). Results in this study showed that clinical T, clinical N stage, and molecular subtypes were not statistically significant predictors of recurrence in patients who achieved pCR after NAC. In spite of that, pCR after NAC may be more important than clinical staging and molecular subtype in early breast cancer. In addition, escalated treatments for patients with HER2 + or triple-negative tumors would be considered with a strict patient selection strategy to prevent over-treatment as well as achieve pCR.